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Cloud InfrastructureAuto-generatedScore: 46

AWS Resource Access Manager MCP Server

The AWS Resource Access Manager (RAM) API, provided by Amazon Web Services, is a comprehensive service designed to streamline and secure the sharing of AWS resources across multiple accounts within an organization or even with external entities.

Quick Start Summary

The AWS Resource Access Manager MCP server is a Model Context Protocol bridge that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the AWS Resource Access Manager API through natural language. It exposes 10 API endpoints as callable tools, such as AcceptResourceShareInvitation, AssociateResourceShare, AssociateResourceSharePermission, and more. No authentication is required — setup takes approximately 30 seconds. The server uses STDIO transport and can be installed by running npx -y @mcp/amazonaws-com-ram. This integration is sourced from the auto AWS Resource Access Manager OpenAPI specification (v2018-01-04) and has a quality score of 46/99 (fair documentation coverage).

10Endpointstools mapped
NoneAuthopen access
46/99Qualityfair
~30 secSetupno auth
View Hosted Config URLClaude Desktop Setup Guide

Server Details

Category
Cloud Infrastructure
Authentication
None
Endpoints
10 operations
Transport
STDIO
Spec Version
v2018-01-04
Install Command
npx -y @mcp/amazonaws-com-ram

Environment Variables

AWS_RESOURCE_ACCESS_MANAGER_API_KEY

Example: your_aws_resource_access_manager_api_key

Top Endpoints

POST
/acceptresourceshareinvitation

AcceptResourceShareInvitation

POST
/associateresourceshare

AssociateResourceShare

POST
/associateresourcesharepermission

AssociateResourceSharePermission

POST
/createpermission

CreatePermission

POST
/createpermissionversion

CreatePermissionVersion

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📖 Detailed MCP Integration Guide

A technical breakdown of capabilities, agent workflows, and security/configuration best practices.

⚡Capabilities & Use Cases
The AWS Resource Access Manager (RAM) API, provided by Amazon Web Services, is a comprehensive service designed to streamline and secure the sharing of AWS resources across multiple accounts within an organization or even with external entities. It eliminates the need to provision and manage resources in each individual account, thereby reducing operational overhead and promoting resource consolidation. The core capabilities of this API include creating, updating, and deleting resource shares; managing permissions to control which actions principals can perform on shared resources; and handling invitations to accept or reject resource shares. Enterprise use cases typically involve centralizing networking infrastructure like Virtual Private Clouds (VPCs) and Transit Gateways, sharing datasets stored in AWS Lake Formation, or distributing standard machine learning models across development teams. For consumers, it enables simplified access to centrally managed tools or data without requiring direct ownership of the underlying infrastructure.
🤖AI Agent Value
When exposed as tools to an AI coding assistant via the Model Context Protocol (MCP), this API unlocks significant value by transforming static infrastructure management into a dynamic, conversational, and automated workflow. The AI agent can act as a specialized cloud administrator, interpreting natural language commands to execute precise API actions. This allows developers to offload complex, multi-step resource provisioning and permissioning tasks to the AI, drastically reducing cognitive load and the potential for manual error. For instance, instead of manually navigating the AWS Console or writing extensive CLI scripts, a developer can describe the desired end state in plain language, and the AI can orchestrate the necessary API calls—such as creating a permission, attaching it to a resource share, and inviting another account—all within a single interactive session.
💬Example Workflows
Practical workflow examples enabled by this MCP server are both numerous and impactful. A developer could instruct the AI agent to "create a new resource share for our shared services VPC and grant read-only access to the network operations account," prompting the AI to sequentially call the CreateResourceShare, CreatePermission, and AssociateResourceSharePermission endpoints. Another powerful task involves automation; a developer could command, "Scan all active resource shares, identify any sharing a specific RDS database snapshot, and revoke that permission," leading the AI to query, analyze, and execute disassociations or deletions as needed. This capability is particularly valuable for compliance and auditing, as the AI can be tasked to "generate a report of all principals with access to our production database resource share," synthesizing information from multiple API calls into a coherent summary.
🛡️Security & Auth
Critical configuration and security best practices are paramount when deploying this MCP server. Although the API reference might indicate a "None" authentication method, in practice, every RAM API call must be authenticated and authorized using AWS Identity and Access Management (IAM). Developers must ensure the AI assistant operates with credentials (e.g., an IAM role or user) that have the minimum necessary permissions—a strict application of the principle of least privilege. For example, the credentials should only allow actions like ram:CreateResourceShare or ram:AssociateResourceSharePermission on specific resources tagged appropriately, and never have blanket AdministratorAccess. The server configuration should enforce secure credential handling, avoid hardcoding secrets, and ideally use temporary, role-assumed credentials. All actions taken by the AI should be logged via AWS CloudTrail for auditability, ensuring that automated resource sharing remains transparent, controlled, and compliant with organizational security policies.

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